ggplot(
top20_breaches_2024,
aes(x = records_lost, y = reorder(organisation, records_lost))
) +
geom_point(size = 5, aes(color = sector)) +
# label for Ticketmaster
geom_text_repel(
data = top_lab,
aes(label = label_text),
direction = "x", hjust = 0,
min.segment.length = Inf, segment.size = 0,
box.padding = 0.1, point.padding = 0.2,
seed = 123
) +
# use Okabe–Ito (color-blind friendly)
scale_color_manual(values = okabe_ito) +
# force the axis you want, keep extra room for the label
scale_x_continuous(
trans = "log10",
breaks = breaks_vec,
labels = labels_vec,
expand = expansion(mult = c(0.02, 0.28))
) +
coord_cartesian(clip = "off") +
labs(
title = "Figure 2. Principales filtraciones de datos de 2024",
x = "Records Lost",
y = NULL,
color = "Sector",
caption = "Source: McCandless, D. (2022). Los mayores casos de filtración y piratería informática del mun"
) +
# ---- apply your global figure styling ----
theme(
plot.title = element_text(size = rel(1.2)),
axis.title = element_text(size = rel(1.0)),
legend.position = "right",
# match Fig. 1 caption alignment & spacing control
plot.caption.position = "plot",
plot.caption = element_text(hjust = 1, margin = margin(t = 20)),
# optional: lighten grid to match your fig 1 feel
panel.grid.major.y = element_line(linetype = "dashed", color = "gray80"),
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank()
)
Bio
Olivia is a graduate from the Australian National University (ANU), acquiring an interdisciplinary double degree in philosophy and natural resource management. At the ALA, she works as a support officer with a primary focus on monitoring the research impact of the Atlas. She is passionate about accessibility, environmental justice and diversity in STEMM.
Posts
Counting points in multipolygon shapefiles for choropleth mapping
Choropleth maps are an excellent way to visualise numbers of observations in each region. When using point data, calculating the number of points in each polygon can be difficult when using shapefiles. Here we demonstrate how to extract and summarise the number of points in each polygon within a shapefile to create a choropleth map.
